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- Title
Regional Economic Development Trend Prediction Method Based on Digital Twins and Time Series Network.
- Authors
Runguo Xu; Xuehan Yu; Xiaoxue Zhao
- Abstract
At present, the interpretation of regional economic development (RED) has changed from a simple evaluation of economic growth to a focus on economic growth and the optimization of economic structure, the improve)ment of economic relations, and the change of institutional innovation. This article uses the RED trend as the research object and constructs the RED index to conduct the theoretical analysis. Then this paper uses the attention mechanism based on digital twins and the time series network model to verify the actual data. Finally, the regional economy is predicted according to the theoretical model. The specific research work mainly includes the following aspects: 1) This paper introduced the development status of research on time series networks and economic forecasting at home and abroad. 2) This paper introduces the basic principles and structures of long and short-term memory (LSTM) and convolutional neural network (CNN), constructs an improved CNN-LSTM model combined with the attention mechanism, and then constructs a regional economic prediction index system. 3) The best parameters of the model are selected through experiments, and the trained model is used for simulation experiment prediction. The results show that the CNN-LSTM model based on the attention mechanism proposed in this paper has high accuracy in predicting regional economies.
- Subjects
REGIONAL development; DIGITAL twins; CONVOLUTIONAL neural networks; TIME series analysis; ECONOMIC development; ECONOMIC forecasting
- Publication
Computers, Materials & Continua, 2023, Vol 76, Issue 2, p1781
- ISSN
1546-2218
- Publication type
Article
- DOI
10.32604/cmc.2023.037293